导弹控制系统的随机混合自适应方案研究

本文提出了一种新的适用于战术导弹控制系统的随机系统控制方案——最小方差混合自校正控制。在这种方案中,具有随机干扰噪声的控制对象保持连续时间状态,而控制参数的估计和调整是离散的,控制规律则是连续和离散变量的混合,整个系统为混合随机系统。由于这类系统具有连续系统和离散系统二者的优点,因而是一种很有前途的控制系统。文中介绍了这种控制方案的基本原理,并以地空导弹自动驾驶仪作为例子进行了数字仿真。仿真结果表明,这种混合自适应方案的跟踪性能优于相类似的全离散自适应方案。当系统阻尼较小时,即在导弹飞行的高空段,这一优点显得尤为突出。     

带伺服滑环和空气静压轴承的转台主轴干扰力矩的实验研究

带滑环伺服系统且采用空气静压气浮轴承的高精度陀螺漂移伺服转台，其控制精度受到气浮轴承粘滞力矩、涡流力矩、轴系质量配置不当造成的静不平衡力矩和滑环伺服系统对主轴干扰力矩的影响。本文通过理论分析和实验研究认为，当主轴轴系垂直于地面放置时，其主要干扰力矩来自滑环伺服系统。论文在对实验数据进行各项检验和处理的基础上给出了主轴常值和随机干扰力矩的数学表达式，为进一步提高同类伺服转台的伺服精度提供了一条有效的途径。     

航空发动机神经网络内模控制

基于神经网络内模控制理论研究了神经网络内模控制方法在航空发动机控制系统中的应用,建立了基于Elman网络的航空发动机多变量内模控制系统。采用Elman网络建立发动机内模型和内模控制器,详细介绍了建模、控制的算法及其实现过程。取部分飞行条件下的数据作为学习样本,采用动态BP算法对神经网络权值进行调整,并在飞行包线内其它工作点对整个控制系统进行了仿真。结果表明,使用神经网络建立的航空发动机内模控制系统具有良好的控制品质和较强的自适应能力。      

Obstacle avoidance handling and mixed integer predictive control for space robots

This paper presents a novel obstacle avoidance constraint and a mixed integer predictive control (MIPC) method for space robots avoiding obstacles and satisfying physical limits during performing tasks. Firstly, a novel kind of obstacle avoidance constraint of space robots, which needs the assumption that the manipulator links and the obstacles can be represented by convex bodies, is proposed by limiting the relative velocity between two closest points which are on the manipulator and the obstacle, respectively. Furthermore, the logical variables are introduced into the obstacle avoidance constraint, which have realized the constraint form is automatically changed to satisfy different obstacle avoidance requirements in different distance intervals between the space robot and the obstacle. Afterwards, the obstacle avoidance constraint and other system physical limits, such as joint angle ranges, the amplitude boundaries of joint velocities and joint torques, are described as inequality constraints of a quadratic programming (QP) problem by using the model predictive control (MPC) method. To guarantee the feasibility of the obtained multi-constraint QP problem, the constraints are treated as soft constraints and assigned levels of priority based on the propositional logic theory, which can realize that the constraints with lower priorities are always firstly violated to recover the feasibility of the QP problem. Since the logical variables have been introduced, the optimization problem including obstacle avoidance and system physical limits as prioritized inequality constraints is termed as MIPC method of space robots, and its computational complexity as well as possible strategies for reducing calculation amount are analyzed. Simulations of the space robot unfolding its manipulator and tracking the end-effector’s desired trajectories with the existence of obstacles and physical limits are presented to demonstrate the effectiveness of the proposed obstacle avoidance strategy and MIPC control method of space robots.     

基于模型重构的变形叶片配准定位技术

叶片毛坯的精确定位是叶片数控加工的核心问题,为了提高叶片数控加工质量,保证叶片各处余量分配均匀,本文以叶片进排气边的自适应数控加工中的检测定位为研究对象,提出了一种基于模型重构的配准定位方法.该方法利用偏置模型的叶片测量方式提高了测量精度,对基于重构的测量模型进行变形与定位分析,得出较优的定位参数.通过仿真试验和对比分析,论证了本文方法的正确性.     

基于模型大扭角叶片的三维矢量测量技术

针对接触式坐标测量机测量大扭角叶片截面存在余弦误差的问题，提出了基于模型的矢量测量方法。本文对此方法的测量精度及测量效率等方面进行论述，并通过实例验证了基于模型的矢量测量方法在精度与效率等方面优势，实现了此测量方法的工程化应用。     

风机叶片静载荷和模态测试技术

对近期国内外在风机叶片静载荷测试和模态测试方面的研究成果、测试标准和测试机构进行了评述.     

Trajectory tracking control of a VTOL unmanned aerial vehicle using offset-free tracking MPC

Designing a stable and robust flight control system for an Unmanned Aerial Vehicle (UAV) is an arduous task. This paper addresses the trajectory tracking control problem of a Ducted Fan UAV (DFUAV) using offset-free Model Predictive Control (MPC) technique in the presence of various uncertainties and external disturbances. The designed strategy aims to ensure adequate flight robustness and stability while overcoming the effects of time delays, parametric uncertainties, and disturbances. The six degrees of freedom DFUAV model is divided into three flight modes based on its airspeed, namely the hover, transition, and cruise mode. The Dryden wind turbulence is applied to the DFUAV in the linear and angular velocity component. Moreover, different uncertainties such as parametric, time delays in state and input, are introduced in translational and rotational components. From the previous work, the Linear Quadratic Tracker with Integrator (LQTI) is used for comparison to corroborate the performance of the designed controller. Simulations are computed to investigate the control performance for the aforementioned modes and different flight phases including the autonomous flight to validate the performance of the designed strategy. Finally, discussions are provided to demonstrate the effectiveness of the given methodology.     

损失及落后角代理模型在多级轴流压气机特性预测中的应用

为了提高轴流压气机设计能力,进而提高发动机的特性,需要掌握一种能够较好预测轴流压气机的压比、效率等特性的方法。结合运用三元流动理论和传统损失落后角模型计算出的压气机流场数据,利用正则化径向基函数神经网络取代经验公式搭建了一种新的损失及落后角模型,计算了E3十级高压压气机的特性;并分别研究了不进行正则化和进行正则化对损失及落后角预测的影响与其对压气机效率和压比特性预测的影响。结果表明,在多级压气机中,在训练样本区分转静子、区分转速、区分工况条件下,使用正则化的径向基神经网络代理模型在大部分情况下能够较好地预测损失、落后角及多级压气机整体特性,但是对沿叶高分布的损失及落后角预测能力还有待提高。